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Merged
merged 2 commits into from
Oct 17, 2019
Merged

Standardize lambda with other frameworks #601

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d9f2f7f
Standardize lambda with other frameworks
seanpmorgan Oct 16, 2019
12b2b3e
Update test cases
seanpmorgan Oct 17, 2019
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2 changes: 1 addition & 1 deletion tensorflow_addons/activations/hardshrink.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@

@keras_utils.register_keras_custom_object
@tf.function
def hardshrink(x, lower=-1.0, upper=1.0):
def hardshrink(x, lower=-0.5, upper=0.5):
"""Hard shrink function.

Computes hard shrink function:
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6 changes: 3 additions & 3 deletions tensorflow_addons/activations/hardshrink_test.py
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Expand Up @@ -37,13 +37,13 @@ def test_invalid(self):
("float32", np.float32),
("float64", np.float64))
def test_hardshrink(self, dtype):
x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype)
x = tf.constant([-2.0, -0.5, 0.0, 0.5, 2.0], dtype=dtype)
expected_result = tf.constant([-2.0, 0.0, 0.0, 0.0, 2.0], dtype=dtype)
self.assertAllCloseAccordingToType(hardshrink(x), expected_result)

expected_result = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype)
expected_result = tf.constant([-2.0, 0.0, 0.0, 0.0, 2.0], dtype=dtype)
self.assertAllCloseAccordingToType(
hardshrink(x, lower=-0.5, upper=0.5), expected_result)
hardshrink(x, lower=-1.0, upper=1.0), expected_result)

@parameterized.named_parameters(("float32", np.float32),
("float64", np.float64))
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2 changes: 1 addition & 1 deletion tensorflow_addons/activations/softshrink.py
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Expand Up @@ -27,7 +27,7 @@

@keras_utils.register_keras_custom_object
@tf.function
def softshrink(x, lower=-1.0, upper=1.0):
def softshrink(x, lower=-0.5, upper=0.5):
"""Soft shrink function.

Computes soft shrink function:
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6 changes: 3 additions & 3 deletions tensorflow_addons/activations/softshrink_test.py
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Expand Up @@ -38,12 +38,12 @@ def test_invalid(self):
("float64", np.float64))
def test_softshrink(self, dtype):
x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype)
expected_result = tf.constant([-1.0, 0.0, 0.0, 0.0, 1.0], dtype=dtype)
expected_result = tf.constant([-1.5, -0.5, 0.0, 0.5, 1.5], dtype=dtype)
self.assertAllCloseAccordingToType(softshrink(x), expected_result)

expected_result = tf.constant([-1.5, -0.5, 0.0, 0.5, 1.5], dtype=dtype)
expected_result = tf.constant([-1.0, 0.0, 0.0, 0.0, 1.0], dtype=dtype)
self.assertAllCloseAccordingToType(
softshrink(x, lower=-0.5, upper=0.5), expected_result)
softshrink(x, lower=-1.0, upper=1.0), expected_result)

@parameterized.named_parameters(("float32", np.float32),
("float64", np.float64))
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8 changes: 4 additions & 4 deletions tensorflow_addons/custom_ops/activations/cc/ops/hardshrink_op.cc
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Expand Up @@ -24,17 +24,17 @@ REGISTER_OP("Addons>Hardshrink")
.Input("features: T")
.Output("activations: T")
.Attr("T: {half, float, double}")
.Attr("lower: float = -1.0")
.Attr("upper: float = 1.0")
.Attr("lower: float = -0.5")
.Attr("upper: float = 0.5")
.SetShapeFn(shape_inference::UnchangedShape);

REGISTER_OP("Addons>HardshrinkGrad")
.Input("gradients: T")
.Input("features: T")
.Output("backprops: T")
.Attr("T: {half, float, double}")
.Attr("lower: float = -1.0")
.Attr("upper: float = 1.0")
.Attr("lower: float = -0.5")
.Attr("upper: float = 0.5")
.SetShapeFn(shape_inference::MergeBothInputsShapeFn);

} // namespace addons
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8 changes: 4 additions & 4 deletions tensorflow_addons/custom_ops/activations/cc/ops/softshrink_op.cc
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Expand Up @@ -24,17 +24,17 @@ REGISTER_OP("Addons>Softshrink")
.Input("features: T")
.Output("activations: T")
.Attr("T: {half, float, double}")
.Attr("lower: float = -1.0")
.Attr("upper: float = 1.0")
.Attr("lower: float = -0.5")
.Attr("upper: float = 0.5")
.SetShapeFn(shape_inference::UnchangedShape);

REGISTER_OP("Addons>SoftshrinkGrad")
.Input("gradients: T")
.Input("features: T")
.Output("backprops: T")
.Attr("T: {half, float, double}")
.Attr("lower: float = -1.0")
.Attr("upper: float = 1.0")
.Attr("lower: float = -0.5")
.Attr("upper: float = 0.5")
.SetShapeFn(shape_inference::MergeBothInputsShapeFn);

} // namespace addons
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